Dear all,

I am trying to fill a matrix, whose rows corresponds to independent multivariate normal random variables. I have tried to following:

```
data {
int<lower=1> J;
int<lower =1> K;
vector[K] mu_a; // mean vector of a
}
parameters{
matrix[J,K] a;
}
model{
to_vector(a) ~ normal(mu_a, rep_vector(5.0, K));
}
```

```
stan_data <- list(J = 2,
K = 8,
mu_a = c(log(1.4e6), log(6.66e-11), log(6),log(5), log(1e4), log(3.7),log(4e4),log(1e-4)),
)
fit_model <- stan("model_code.stan",
data = stan_data,
chains = 1, iter = 1000,
seed=4838282)
```

I am getting the following error:

```
Chain 1: Unrecoverable error evaluating the log probability at the initial value.
Chain 1: Exception: normal_lpdf: Location parameter has dimension = 8, expecting dimension = 16; a function was called with arguments of different scalar, array, vector, or matrix types, and they were not consistently sized; all arguments must be scalars or multidimensional values of the same shape.
```

How do I overcome this error?

Am I correct to say that the code in the model block fills each row of matrix a with independent multivariate normal random vector?

please help.

Thanks